Anomaly Based Distributed Denial of Service Attack Detection and Prevention with Machine Learning

被引：0

作者：

Dincalp, Uygar ^{[1
]}

Guzel, Mehmet Serdar ^{[1
]}

Sevinc, Omer ^{[2
]}

Bostanci, Erkan ^{[1
]}

Askerzade, Iman ^{[1
]}

机构：

[1] Ankara Univ, Dept Comp Engn, Ankara, Turkey

[2] 19 Mayis Univ, Comp Prog Dept, Samsun, Turkey

来源：

2018 2ND INTERNATIONAL SYMPOSIUM ON MULTIDISCIPLINARY STUDIES AND INNOVATIVE TECHNOLOGIES (ISMSIT) | 2018年

关键词：

ddos attack; DBSCAN; machine learning;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Everyday, the DoS/DDoS attacks are increasing all over the world and the ways attackers are using changing continuously. This increase and variety on the attacks are affecting the governments, institutions, organizations and corporations in a bad way. Every successful attack is causing them to lose money and lose reputation in return. This paper presents an introduction to a method which can show what the attack and where the attack based on. This is tried to be achieved with using clustering algorithm DBSCAN on network traffic because of the change and variety in attack vectors.

引用

页码：600 / 603

页数：4

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